In between-attribute Stroop matching tasks, participants compare the meaning (or the color) of a Stroop stimulus with a probe color (or meaning) while attempting to ignore the Stroop stimulus's task-irrelevant attribute. Interference in this task has been explained by two competing theories: A semantic competition account and a response competition account. Recent results favor the response competition account, which assumes that interference is caused by a task-irrelevant comparison. However, the comparison of studies is complicated by the lack of a consensus on how trial types should be classified and analyzed. In this work, we review existing findings and theories and provide a new classification of trial types. We report two experiments that demonstrate the superiority of the response competition account in explaining the basic pattern of performance while also revealing its limitations. Two qualitatively distinct interference patterns are identified, resulting from different types of task-irrelevant comparisons. By finding the same interference pattern across task versions, we were additionally able to demonstrate the comparability of processes across two task versions frequently used in neurophysiological and cognitive studies. An integrated account of both types of interference is presented and discussed.
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http://dx.doi.org/10.3758/s13414-016-1253-x | DOI Listing |
Therapie
December 2024
Science Po, université Paris-Cité, 75006 Paris, France.
France has been engaged in a legal and organisational transition for many years. It has had to adapt its national framework to the legal requirements of personal data protection, European ambitions and international competition. From the Data Protection Act of 1978 to the Healthcare System Transformation Act of 2019, reforms have strengthened requirements in terms of personal data protection, while opening the way to innovative uses.
View Article and Find Full Text PDFPeerJ
January 2025
Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin, China.
With the expansion of the mining industry, environmental pollution from microelements (MP) and red mud (RM) has become a pressing issue. While bioremediation offers a cost-effective and sustainable solution, plant growth in these polluted environments remains difficult. is one of the few plants capable of surviving in RM-affected soils.
View Article and Find Full Text PDFAcc Chem Res
January 2025
Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
ConspectusReactions of gas phase molecules with surfaces play key roles in atmospheric and environmental chemistry. Reactive uptake coefficients (γ), the fraction of gas-surface collisions that yield a reaction, are used to quantify the kinetics in these heterogeneous and multiphase systems. Unlike rate coefficients for homogeneous gas- or liquid-phase reactions, uptake coefficients are system- and observation-dependent quantities that depend upon a multitude of underlying elementary steps.
View Article and Find Full Text PDFIntroduction: Prior studies have demonstrated racial disparities in access to liver transplantation but determinants of these disparities remain poorly understood. We used geographic catchment areas for transplant centers (transplant referral regions, TRRs) to characterize transplant environment contributors to racial and ethnic disparities in liver transplant access.
Methods: Data were obtained from the Scientific Registry for Transplant Recipients (SRTR) and the National Center for Health Statistics (NCHS) from 2015 to 2021.
Cancers (Basel)
December 2024
65+ Outpatient Clinic, Amalia Fleming General Hospital, 14, 25th Martiou Str., 15127 Melissia, Greece.
: Melanoma, an aggressive form of skin cancer, accounts for a significant proportion of skin-cancer-related deaths worldwide. Early and accurate differentiation between melanoma and benign melanocytic nevi is critical for improving survival rates but remains challenging because of diagnostic variability. Convolutional neural networks (CNNs) have shown promise in automating melanoma detection with accuracy comparable to expert dermatologists.
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